Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Publication Tags

These publication tags are generated from the output of this researcher. Click any tag below to view other Huck researchers working on the same topic.

Learning Soil Moisture Convolutional Neural Networks Semantics Travel Time Neurons Big Data Moisture Trajectories Pixels Baseline Prolongation Science Coding Neural Networks Opinion Crime Hydrology Brain Trajectory Availability Experiments Weather Forecasting Network Architecture Climate

Most Recent Publications

Reply to Muralidhar et al., Kenny et al., and Hotz et al.: The benefits of engagement with external research teams

Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian Schmutte, Victoria A. Velkoff, Pavel I. Zhuravlev, 2024, Proceedings of the National Academy of Sciences of the United States of America on p. e2401501121

EXACT PRIVACY ANALYSIS OF THE GAUSSIAN SPARSE HISTOGRAM MECHANISM

Brian Karrer, Daniel Kifer, Arjun Wilkins, Danfeng Zhang, 2024, Journal of Privacy and Confidentiality

Backpropagation-Free Deep Learning with Recursive Local Representation Alignment

Alexander G. Ororbia, Ankur Mali, Daniel Kifer, C. Lee Giles, 2023, on p. 9327-9335

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Prabhav Borate, Jacques Rivière, Chris Marone, Ankur Mali, Daniel Kifer, Parisa Shokouhi, 2023, Nature Communications

An in-depth examination of requirements for disclosure risk assessment

Ron S. Jarmin, John M. Abowd, Robert Ashmead, Ryan Cumings-Menon, Nathan Goldschlag, Michael B. Hawes, Sallie Ann Keller, Daniel Kifer, Philip Leclerc, Jerome P. Reiter, Rolando A. Rodríguez, Ian Schmutte, Victoria A. Velkoff, Pavel Zhuravlev, 2023, Proceedings of the National Academy of Sciences of the United States of America

Differentiable modelling to unify machine learning and physical models for geosciences

Chaopeng Shen, Alison P. Appling, Pierre Gentine, Toshiyuki Bandai, Hoshin Gupta, Alexandre Tartakovsky, Marco Baity-Jesi, Fabrizio Fenicia, Daniel Kifer, Li Li, Xiaofeng Liu, Wei Ren, Yi Zheng, Ciaran J. Harman, Martyn Clark, Matthew Farthing, Dapeng Fang, Dapeng Feng, Praveen Kumar, Doaa Aboelyazeed, Farshid Rahmani, Yalan Song, Hylke E. Beck, Tadd Bindas, Dipankar Dwivedi, Kuai Fang, Marvin Höge, Chris Rackauckas, Binayak Mohanty, Tirthankar Roy, Chonggang Xu, Kathryn Lawson, 2023, Nature Reviews Earth and Environment on p. 552-567

An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions

Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer, 2023,

Answering Private Linear Queries Adaptively using the Common Mechanism

Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2023, Proceedings of the VLDB Endowment on p. 1883-1896

The neural coding framework for learning generative models

Alexander Ororbia, Daniel Kifer, 2022, Nature Communications

Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms

Zeyu Ding, Yuxin Wang, Wang Yuxin, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, D Kifer, Daniel Kifer, 2022, VLDB Journal on p. 23-48

Most-Cited Papers

Pufferfish: A framework for mathematical privacy definitions

Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, Clyde Giles, 2017, on p. 4342–4351

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

A Simple Baseline for Travel Time Estimation using Large-scale Trip Data

Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology

A neural temporal model for human motion prediction

Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117

Concentrated differentially private gradient descent with adaptive per-iteration privacy budget

Jaewoo Lee, Daniel Kifer, 2018, on p. 1656-1665

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection

Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261